INF2D: 28: Decision Making Under Uncertainty
We now start to combine the probabilistic model of belief that we have been studying for the past few weeks with a numeric representation of preferences, to build a model of rational decision making in an uncertain environment. This folder presents how to represent and reason about decision making in a static uncertain environment. So it combines a representation of (probabilistic) belief as a Bayesian Network with a Utility Function. This combination is known as a Decision Network.
Lecture Slides
Previous Year's "Notes" Version
Required Reading
R&N Section 16.1–16.3, 16.5 or NIE Chapter (16) "Making Simple Decisions", Sections 1–3 and 5.
NOTE: The abbreviation R&N refers to:
“Artificial Intelligence: A Modern Approach” Third Edition, Russell R & Norvig P, Prentice Hall, 2010 (R&N).
The abbreviation NIE stands for the following edition of the same book:
“Artificial Intelligence: A Modern Approach” Third Edition, Pearson New International Edition, Russell R & Norvig P, Pearson, 2014.